The present invention relates to a decentralized management platform.
One goal of an energy management system (EMS) in power networks is to balance the supply and demand in a cost efficient manner given its operating horizon, and uncertainties in generation due to renewable generators and in demand. There are centralized approaches available in the literature to solve this problem. However, they are not scalable. To add any new device into the energy system, the centralized management systems need to be interrupted, updated and remodeled for any specific new change in the system model. Moreover, as to reliability, any malfunction of the central controller and/or any device results can disrupt the operation of the whole system. There are also some distributed management methods which mostly employ heuristic algorithms. However, these approaches cannot analytically guarantee the optimality of the solution, reliability, and scalability of the system.
Moreover, management of energy systems in community level including distributed generations (DGs) and storage devices can be challenging due to intermittent and uncontrollable nature of many types of DGs, energy sources with different rates, and the following issues:                1. Scalability: The community-level energy systems are large in size, and are also capable to grow more and add new components during their lifetime. Adding any new device introduces new set of parameters, objectives, and constraints in the operation of these systems. As a result, the management platform should be able to integrate the new devices without any interruption for updating its control algorithm.        2. Reliability: The malfunction of any device in the system should not result in an interrupt in the operation of the whole system. According to DOE reliability requirements, management systems should guarantee at least 98% reliability to supply critical loads without any outage times.        3. Efficiency: Due to large size of the management problem for these systems, achieving long-term optimal total cost and real-time operation of energy systems is another challenge for management systems.        